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Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and E-tongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis.
A “turn-on” fluorescence sensing system based on a BODIPY-cobaloxime complex for the detection of H2S in liquid and gas phase was developed. To that aim, two cobaloxime complexes bearing an axial pyridyl-BODIPY ligand were initially evaluated as sensitive fluorescent HS− indicators in aqueous solution. The sensing mechanism involves the selective substitution of the BODIPY ligand by the HS− anion at the cobalt center, which is accompanied by a strong fluorescence enhancement. The selection of a complex with an ideal stability and reactivity profile toward HS− relied on the optimal interaction between the cobalt metal-center and two different pyridyl BODIPY ligands. Loading the best performing BODIPY-cobaloxime complex onto a polymeric hydrogel membrane allowed us to study the selectivity of the probe for HS− against different anions and cysteine. Successful detection of H2S by the fluorescent “light-up” membrane was not only accomplished for surface water but could also be demonstrated for relevant H2S concentrations in gas phase.
Using a swarm of copter-based gas-sensitive aerial nano robots for monitoring indoor air quality is challenging due to, e.g., limited air space in buildings. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined to guarantee a safe operation of the swarm.
The key contributions of this poster are the realization of experiments that investigate the influence of the rotor downwash on flying vertically displaced nano robots and the development of a model describing the above-mentioned safety region.
Using a swarm of copter-based gas-sensitive aerial nano robots for monitoring indoor air quality is challenging due to, e.g., limited air space in buildings. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined to guarantee a safe operation of the swarm.
The key contributions of this paper are the realization of experiments that investigate the influence of the rotor downwash on flying vertically displaced nano robots and the development of a model describing the above-mentioned safety region.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
Fluorometric sensing is a versatile approach for trace analysis outside of the laboratory, requiring suitable sensor materials and their integration into sensing devices. The versatility of fluorophores as probes, especially in terms of the possibility to tailor their optical as well as their recognition properties by synthetic modifications in a wide range, renders them as superior active component for the preparation of optical sensing devices. Recent works at BAM in this field include, for example, the detection of nerve gas agents, illustrating impressively the aforementioned benefits of fluorophores in optical sensing applications.
In the interdisciplinary project presented here, we target hazardous gases such as ammonia, benzene, and hydrogen sulfide, next to others, which pose a major threat to human health and environmental safety and for which the availability of a sensitive and reliable detection method is highly desirable. The dyes presented follow a “turn-on” fluorescence schematic, which allows for the selective and sensitive detection of the respective gaseous analyte. The immobilization of the probe in polymeric matrices is then the next step toward the fabrication of a prototype device for molecular sensing. Further steps in the project include the assembly of instruments for test-atmosphere generation, the referencing of the sensor system, development and implementation of an optical setup, and the testing of the prototype device under laboratory conditions and in the field.
In this presentation, we give an overview over the recent developments on this topic in our groups. Highlights are hydrogen sulfide sensitive, BODIPY based transition metal complexes, which allow for a sensitive as well as selective detection of the toxic gas. In addition, we present a novel class of highly substituted BODIPY derivatives – pocket-BODIPYs – which are of a synthetically high versatility and can readily be modified to create pockets in the periphery of the molecule of defined geometries. This is illustrated on the successful encapsulation of benzene by a pocket-BODIPY derivative, confirmed by X-ray crystallographic analysis as well as by further spectroscopic and analytical methods.
Fluorescence based sensing is a versatile approach for the trace analysis outside of the laboratory, requiring suitable sensor materials and their integration into sensing devices. The versatility of fluorophores as probes, especially in terms of the possibility to tailor their optical as well as their recognition properties by synthetic modifications in a wide range, renders them a superior active component for the preparation of optical sensor devices. Recent works at BAM in this field include, for example, the detection of nerve gas agents, illustrating impressively the aforementioned benefits of fluorophores in optical sensing applications.
In the interdisciplinary approach presented here, we target hazardous gases such as ammonia, benzene, and hydrogen sulfide, next to others, which pose a major threat to human health and environmental safety and for which the availability of a sensitive and reliable detection method is highly desirable.
The dyes presented follow a “turn-on” fluorescence schematic which allows for the selective and sensitive detection of the respective gaseous analyte. The immobilization of the probe in polymeric matrices is then the next step toward the fabrication of a prototype device for molecular sensing.